399 lines
12 KiB
Python
399 lines
12 KiB
Python
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"""
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Singularities
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=============
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This module implements algorithms for finding singularities for a function
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and identifying types of functions.
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The differential calculus methods in this module include methods to identify
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the following function types in the given ``Interval``:
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- Increasing
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- Strictly Increasing
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- Decreasing
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- Strictly Decreasing
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- Monotonic
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"""
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from sympy.core.power import Pow
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from sympy.core.singleton import S
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from sympy.core.symbol import Symbol
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from sympy.core.sympify import sympify
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from sympy.functions.elementary.exponential import log
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from sympy.functions.elementary.trigonometric import sec, csc, cot, tan, cos
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from sympy.utilities.misc import filldedent
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def singularities(expression, symbol, domain=None):
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"""
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Find singularities of a given function.
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Parameters
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==========
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expression : Expr
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The target function in which singularities need to be found.
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symbol : Symbol
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The symbol over the values of which the singularity in
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expression in being searched for.
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Returns
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=======
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Set
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A set of values for ``symbol`` for which ``expression`` has a
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singularity. An ``EmptySet`` is returned if ``expression`` has no
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singularities for any given value of ``Symbol``.
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Raises
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======
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NotImplementedError
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Methods for determining the singularities of this function have
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not been developed.
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Notes
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=====
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This function does not find non-isolated singularities
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nor does it find branch points of the expression.
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Currently supported functions are:
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- univariate continuous (real or complex) functions
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References
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==========
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.. [1] https://en.wikipedia.org/wiki/Mathematical_singularity
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Examples
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========
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>>> from sympy import singularities, Symbol, log
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>>> x = Symbol('x', real=True)
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>>> y = Symbol('y', real=False)
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>>> singularities(x**2 + x + 1, x)
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EmptySet
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>>> singularities(1/(x + 1), x)
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{-1}
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>>> singularities(1/(y**2 + 1), y)
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{-I, I}
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>>> singularities(1/(y**3 + 1), y)
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{-1, 1/2 - sqrt(3)*I/2, 1/2 + sqrt(3)*I/2}
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>>> singularities(log(x), x)
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{0}
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"""
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from sympy.solvers.solveset import solveset
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if domain is None:
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domain = S.Reals if symbol.is_real else S.Complexes
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try:
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sings = S.EmptySet
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for i in expression.rewrite([sec, csc, cot, tan], cos).atoms(Pow):
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if i.exp.is_infinite:
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raise NotImplementedError
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if i.exp.is_negative:
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sings += solveset(i.base, symbol, domain)
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for i in expression.atoms(log):
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sings += solveset(i.args[0], symbol, domain)
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return sings
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except NotImplementedError:
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raise NotImplementedError(filldedent('''
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Methods for determining the singularities
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of this function have not been developed.'''))
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###########################################################################
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# DIFFERENTIAL CALCULUS METHODS #
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###########################################################################
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def monotonicity_helper(expression, predicate, interval=S.Reals, symbol=None):
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"""
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Helper function for functions checking function monotonicity.
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Parameters
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==========
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expression : Expr
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The target function which is being checked
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predicate : function
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The property being tested for. The function takes in an integer
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and returns a boolean. The integer input is the derivative and
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the boolean result should be true if the property is being held,
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and false otherwise.
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interval : Set, optional
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The range of values in which we are testing, defaults to all reals.
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symbol : Symbol, optional
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The symbol present in expression which gets varied over the given range.
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It returns a boolean indicating whether the interval in which
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the function's derivative satisfies given predicate is a superset
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of the given interval.
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Returns
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=======
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Boolean
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True if ``predicate`` is true for all the derivatives when ``symbol``
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is varied in ``range``, False otherwise.
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"""
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from sympy.solvers.solveset import solveset
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expression = sympify(expression)
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free = expression.free_symbols
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if symbol is None:
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if len(free) > 1:
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raise NotImplementedError(
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'The function has not yet been implemented'
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' for all multivariate expressions.'
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)
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variable = symbol or (free.pop() if free else Symbol('x'))
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derivative = expression.diff(variable)
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predicate_interval = solveset(predicate(derivative), variable, S.Reals)
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return interval.is_subset(predicate_interval)
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def is_increasing(expression, interval=S.Reals, symbol=None):
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"""
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Return whether the function is increasing in the given interval.
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Parameters
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==========
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expression : Expr
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The target function which is being checked.
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interval : Set, optional
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The range of values in which we are testing (defaults to set of
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all real numbers).
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symbol : Symbol, optional
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The symbol present in expression which gets varied over the given range.
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Returns
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=======
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Boolean
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True if ``expression`` is increasing (either strictly increasing or
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constant) in the given ``interval``, False otherwise.
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Examples
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========
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>>> from sympy import is_increasing
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>>> from sympy.abc import x, y
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>>> from sympy import S, Interval, oo
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>>> is_increasing(x**3 - 3*x**2 + 4*x, S.Reals)
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True
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>>> is_increasing(-x**2, Interval(-oo, 0))
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True
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>>> is_increasing(-x**2, Interval(0, oo))
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False
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>>> is_increasing(4*x**3 - 6*x**2 - 72*x + 30, Interval(-2, 3))
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False
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>>> is_increasing(x**2 + y, Interval(1, 2), x)
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True
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"""
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return monotonicity_helper(expression, lambda x: x >= 0, interval, symbol)
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def is_strictly_increasing(expression, interval=S.Reals, symbol=None):
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"""
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Return whether the function is strictly increasing in the given interval.
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Parameters
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==========
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expression : Expr
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The target function which is being checked.
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interval : Set, optional
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The range of values in which we are testing (defaults to set of
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all real numbers).
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symbol : Symbol, optional
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The symbol present in expression which gets varied over the given range.
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Returns
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=======
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Boolean
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True if ``expression`` is strictly increasing in the given ``interval``,
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False otherwise.
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Examples
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========
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>>> from sympy import is_strictly_increasing
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>>> from sympy.abc import x, y
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>>> from sympy import Interval, oo
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>>> is_strictly_increasing(4*x**3 - 6*x**2 - 72*x + 30, Interval.Ropen(-oo, -2))
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True
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>>> is_strictly_increasing(4*x**3 - 6*x**2 - 72*x + 30, Interval.Lopen(3, oo))
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True
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>>> is_strictly_increasing(4*x**3 - 6*x**2 - 72*x + 30, Interval.open(-2, 3))
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False
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>>> is_strictly_increasing(-x**2, Interval(0, oo))
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False
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>>> is_strictly_increasing(-x**2 + y, Interval(-oo, 0), x)
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False
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"""
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return monotonicity_helper(expression, lambda x: x > 0, interval, symbol)
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def is_decreasing(expression, interval=S.Reals, symbol=None):
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"""
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Return whether the function is decreasing in the given interval.
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Parameters
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==========
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expression : Expr
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The target function which is being checked.
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interval : Set, optional
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The range of values in which we are testing (defaults to set of
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all real numbers).
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symbol : Symbol, optional
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The symbol present in expression which gets varied over the given range.
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Returns
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=======
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Boolean
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True if ``expression`` is decreasing (either strictly decreasing or
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constant) in the given ``interval``, False otherwise.
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Examples
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========
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>>> from sympy import is_decreasing
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>>> from sympy.abc import x, y
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>>> from sympy import S, Interval, oo
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>>> is_decreasing(1/(x**2 - 3*x), Interval.open(S(3)/2, 3))
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True
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>>> is_decreasing(1/(x**2 - 3*x), Interval.open(1.5, 3))
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True
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>>> is_decreasing(1/(x**2 - 3*x), Interval.Lopen(3, oo))
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True
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>>> is_decreasing(1/(x**2 - 3*x), Interval.Ropen(-oo, S(3)/2))
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False
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>>> is_decreasing(1/(x**2 - 3*x), Interval.Ropen(-oo, 1.5))
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False
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>>> is_decreasing(-x**2, Interval(-oo, 0))
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False
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>>> is_decreasing(-x**2 + y, Interval(-oo, 0), x)
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False
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"""
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return monotonicity_helper(expression, lambda x: x <= 0, interval, symbol)
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def is_strictly_decreasing(expression, interval=S.Reals, symbol=None):
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"""
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Return whether the function is strictly decreasing in the given interval.
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Parameters
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==========
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expression : Expr
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The target function which is being checked.
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interval : Set, optional
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The range of values in which we are testing (defaults to set of
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all real numbers).
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symbol : Symbol, optional
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The symbol present in expression which gets varied over the given range.
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Returns
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=======
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Boolean
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True if ``expression`` is strictly decreasing in the given ``interval``,
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False otherwise.
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Examples
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========
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>>> from sympy import is_strictly_decreasing
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>>> from sympy.abc import x, y
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>>> from sympy import S, Interval, oo
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>>> is_strictly_decreasing(1/(x**2 - 3*x), Interval.Lopen(3, oo))
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True
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>>> is_strictly_decreasing(1/(x**2 - 3*x), Interval.Ropen(-oo, S(3)/2))
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False
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>>> is_strictly_decreasing(1/(x**2 - 3*x), Interval.Ropen(-oo, 1.5))
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False
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>>> is_strictly_decreasing(-x**2, Interval(-oo, 0))
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False
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>>> is_strictly_decreasing(-x**2 + y, Interval(-oo, 0), x)
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False
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"""
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return monotonicity_helper(expression, lambda x: x < 0, interval, symbol)
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def is_monotonic(expression, interval=S.Reals, symbol=None):
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"""
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Return whether the function is monotonic in the given interval.
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Parameters
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==========
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expression : Expr
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The target function which is being checked.
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interval : Set, optional
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The range of values in which we are testing (defaults to set of
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all real numbers).
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symbol : Symbol, optional
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The symbol present in expression which gets varied over the given range.
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Returns
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=======
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Boolean
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True if ``expression`` is monotonic in the given ``interval``,
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False otherwise.
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Raises
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======
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NotImplementedError
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Monotonicity check has not been implemented for the queried function.
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Examples
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========
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>>> from sympy import is_monotonic
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>>> from sympy.abc import x, y
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>>> from sympy import S, Interval, oo
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>>> is_monotonic(1/(x**2 - 3*x), Interval.open(S(3)/2, 3))
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True
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>>> is_monotonic(1/(x**2 - 3*x), Interval.open(1.5, 3))
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True
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>>> is_monotonic(1/(x**2 - 3*x), Interval.Lopen(3, oo))
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True
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>>> is_monotonic(x**3 - 3*x**2 + 4*x, S.Reals)
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True
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>>> is_monotonic(-x**2, S.Reals)
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False
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>>> is_monotonic(x**2 + y + 1, Interval(1, 2), x)
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True
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"""
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from sympy.solvers.solveset import solveset
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expression = sympify(expression)
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free = expression.free_symbols
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if symbol is None and len(free) > 1:
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raise NotImplementedError(
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'is_monotonic has not yet been implemented'
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' for all multivariate expressions.'
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)
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variable = symbol or (free.pop() if free else Symbol('x'))
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turning_points = solveset(expression.diff(variable), variable, interval)
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return interval.intersection(turning_points) is S.EmptySet
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